def test_lam(self): likelihood = StudentTLikelihood(self.x, self.y, self.function, nu=0, sigma=0.5) self.assertAlmostEqual(4.0, likelihood.lam)
def test_repr(self): nu = 0 sigma = 0.5 likelihood = StudentTLikelihood( self.x, self.y, self.function, nu=nu, sigma=sigma ) expected = "StudentTLikelihood(x={}, y={}, func={}, nu={}, sigma={})".format( self.x, self.y, self.function.__name__, nu, sigma ) self.assertEqual(expected, repr(likelihood))
def test_log_likelihood_nu_none(self): likelihood = StudentTLikelihood(self.x, self.y, self.function, nu=None) likelihood.parameters["m"] = 2 likelihood.parameters["c"] = 0 with self.assertRaises((ValueError, TypeError)): # ValueError in Python2, TypeError in Python3 likelihood.log_likelihood()
def test_known_sigma(self): likelihood = StudentTLikelihood(self.x, self.y, self.function, self.nu, self.sigma) likelihood.parameters['m'] = 2 likelihood.parameters['c'] = 0 likelihood.log_likelihood() self.assertEqual(likelihood.sigma, self.sigma)
def test_setting_nu_positive_does_not_change_class_attribute(self): likelihood = StudentTLikelihood(self.x, self.y, self.function, nu=None) likelihood.parameters["m"] = 2 likelihood.parameters["c"] = 0 likelihood.parameters["nu"] = 98 self.assertTrue(likelihood.nu == 98)
def test_log_likelihood_nu_negative(self): likelihood = StudentTLikelihood(self.x, self.y, self.function, nu=-1) likelihood.parameters["m"] = 2 likelihood.parameters["c"] = 0 with self.assertRaises(ValueError): likelihood.log_likelihood()
def test_set_nu_none(self): likelihood = StudentTLikelihood(self.x, self.y, self.function, nu=None) likelihood.parameters["m"] = 2 likelihood.parameters["c"] = 0 self.assertTrue(likelihood.nu is None)
def test_log_likelihood_nu_zero(self): likelihood = StudentTLikelihood(self.x, self.y, self.function, nu=0) likelihood.parameters['m'] = 2 likelihood.parameters['c'] = 0 with self.assertRaises(ValueError): likelihood.log_likelihood()